Mini-DAQ: A lightweight, low-cost, high resolution, data acquisition system for wave energy converter testing

Graphical abstract


Hardware description
The Mini-DAQ is an open-source compact data acquisition system intended for laboratory testing of wave energy converters. It interfaces to a variety of sensors to collect data to be sent on an EtherCAT bus to a control and data logging computer. The design is intended to be relatively simple to assemble and easily customizable and replicable. It allows for a lightweight inexpensive compact package to be on the WEC device, close to the sensors and actuators and is highly customizable.
The Mini-DAQ design has interface capability and code for three commonly used sensors in WEC systems.
Four channel differential ± 10 V 16-bit analog to digital (A/D) converter input RS232 serial communication (for example, for interface with an inertial measurement unit (IMU)) Implementation of 4-20 mA pressure sensor capture using precision resistor Additional sensors that have been tested but are outside the scope of this project.
Eight-channel ± 10 V 16-bit digital to analog (D/A) converter output Wheatstone bridge low level voltage input Synchronous Serial Interface (SSI) Digital I/O Quadrature encoder input Two channel 4-20 mA 16-bit current measurement for measuring pressure sensors for example Additional information regarding additional testing of sensors within this framework is available in [7]. In this implementation, an Arduino Mega 2560 [8] is used to interface with signal conditioning. The EasyCAT shield for Arduino [9] allows the Arduino to put data onto the EtherCAT network for logging and control. This constitutes a secondary node on the EtherCAT network. The primary EtherCAT node used in this example is executed by a Speedgoat computer running compiled MATLAB/Simulink code. Potential future work includes the development of a low-cost primary EtherCAT node to be paired with the MiniDAQ. Electrical Component

Build instructions
Install the EasyCAT board onto the controller board as shown in Fig. 1.
Connect the ADC evaluation board to controller board as shown in Fig. 2 with pin assignments in Table 1. This can be done by modifying the included ribbon cable, or by removing the connector from the ADC evaluation board and soldering jumper wires directly to the board. Verify that JP1 on the ADC evaluation board is set to EXT, and JP2 is set to INT. Table 2 Connect MAX232 Board to the controller board as shown in Fig. 2 and Table 1 using jumper wires. Connect the Arduinio Mega 2560 via USB to a computer and program with code Arduino/Arduino.ino. Remove USB cable and connect power with 7-12 V power supply via the barrel connector. Connect xsens IMU to the MAX232 Board via 9 pin D-Sub connector. Connect 4-20 mA pressure sensor to precision resistor as shown in Fig. 3, and connect resistor to ADC1 input from Fig. 2.

Validation and characterization
As a test of the quality of measurement the Mini-DAQ can provide, a direct comparison with an industry standard data acquisition system and oscilloscope was undertaken. The analog to digital converter was used for this study. Four channels of input data were fed from their source to the three acquisition systems. The signals fed are a voltage standard, random delay square wave, sine wave, and bandlimited white noise.
All tests were performed at the O.H. Hinsdale Wave Research Laboratory (HWRL) at Oregon State University. The data acquisition system used in this facility includes a National Instruments PXI system which includes a chassis and controller. Analog data acquisition is controlled by a NI PXI-6259 MÀseries 16-bit multifunction DAQ module. This module is then connected to a SCXI-1143 Butterworth anti-aliasing filter module. This module is then fronted with an SCXI-1305 terminal block that take ±5V differential inputs from analog channels via 50 X coaxial cable with BNC connectors. The SCXI-1143 Butterworth anti-aliasing filters are set with cutoff frequency at ¼ the sampling rate. Unless specifically noted, a sampling rate of 10 ms was used for data capture. Heretofore this data acquisition will be referred to as HWRL.
The oscilloscope used for additional comparison of results is the Tektronix DPO7054 Digital Phosphor Oscilloscope. Captured data was saved locally to the hard drive of the oscilloscope and transferred via USB flash drive for post processing. The data was captured at a sample rate of 10 ms. Heretofore this oscilloscope will be referred to as scope.
The voltage standard is a piece of test equipment typically used in calibration and validation of data acquisition systems and provides a stable constant prescribed voltage. For this test an Analogic AN3100 with a current NIST traceable calibration was used. The voltage was set to a value of 2.71828 V and recorded for one hour with results shown in Fig. 4. Statistical analysis was performed on the three recorded signals of interest and results are shown in Table 1. While the Mini-DAQ has a higher percent error and standard deviation compared to the HWRL and scope, the result indicates values acceptable for most applications.  The next signal of interest recorded was a random delay square wave. This is a signal used in the lab to synchronize datasets captured from different sources. The output signal is split and captured by all relevant systems which allows for time alignment in post processing. In this case, the first rising edge was used to align the three different data captures. The upper left of Fig. 5 shows the beginning of the record with signals aligned on the first rising edge. The upper right of Fig. 5 shows the end of the hour-long record with minimal phase shift between the signals. The lower left of Fig. 5 shows the sine wave at the start of the record and lower right the end, again with minimal phase shift. To quantify the clock drift between the different capture methods, an analysis of the sine wave captured data was undertaken. A zero up-crossing analysis was done and the average timestamp between consecutive up-crossings was recorded for all three signals. As the HWRL data acquisition system was the most sophisticated and trusted source it was treated as the ''truth" to be compared against by the other two signals. In this manner the resulting MiniDAQ and scope timestamps were subtracted from the HWRL timestamps to see how the clocks shifted over time. The top plot in Fig. 6 shows the product specification for the HWRL data acquisition clock at 50 parts per million (ppm). This is to show what would happen if at every clock cycle the clock was off exactly the specification throughout the capture duration. While this is extremely unlikely, it gives a bound to compare the other results to. A linear first order fit was applied to the scope and MiniDAQ signals to estimate a drift in ppm. Scope results show a drift of À8.83 ppm while the MiniDAQ show a drift of 1.22 ppm. These are well inside the HWRL specifications and indicate a reasonable level of clock drift. The bottom plot in Fig. 6 shows the individual periods of the sine wave vs. time giving insight into the variations in periods over time. It is suspected that the low variation in periods achieved by the HWRL DAQ is due to the anti-aliasing filtering being done to the signal at capture. The MiniDAQ and scope do not have an equivalent filtering applied.
Finally, a bandlimited white noise signal was created as an input for analysis. An amplitude of 5 V and a bandlimit of 0.5 to 25 Hz was applied. This signal was only captured with the MiniDAQ and the HWRL DAQ and the power spectral density (PSD) of the recorded signal is show in Fig. 7. The PSD of the input signal is included for comparison. This shows that both the MiniDAQ and HWRL DAQ can capture a signal over the frequency range chosen which corresponds to a typical range for small scale WEC research.